Abstract
Rising greenhouse gas emissions stemming from road transport have intensified the need for efficient and environmentally friendly propulsion technologies. Hybrid and fuel cell electric vehicles have emerged as a viable solution, integrating internal combustion engines and fuel cells with electric motors to optimize fuel efficiency and reduce emissions. This article reviews and analyzes energy management strategies for the principal powertrain topologies of hybrid electric vehicles, focusing on achieving solution optimality in real-time applications. A thorough and comprehensive overview of rule-based, optimization-based, and learning-based energy management strategies is presented, highlighting their main attributes and providing a comparative analysis in terms of fuel economy improvements, real-time implementation feasibility, and computational complexity, while simultaneously identifying and uncovering areas requiring further research in the field. We found that while rule-based methods offer simplicity and real-time capability, their adaptability remains limited. Optimization-based and learning-based approaches, although often achieving near-optimal solutions, face challenges due to their high computational demands and integration complexities. Our analysis also revealed the importance of leveraging vehicle connectivity and intelligent transportation systems for future energy management developments, which will contribute to broader sustainability goals in the automotive sector.
Translated title of the contribution | Optimización del rendimiento de vehículos eléctricos híbridos: una visión detallada de las estrategias de gestión de energía. |
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Original language | English |
Article number | 10 |
Journal | Energies |
Volume | 18 |
Issue number | 10 |
DOIs | |
Publication status | Published - 24 Dec 2024 |
Keywords
- efficiency
- energy management strategies
- fuel cell hybrid electric vehicles
- fuel economy
- greenhouse gas emissions
- hybrid electric vehicles
- optimization
- real-time control
Project and Funding Information
- Funding Info